Respiratory rate estimation during triage of children in hospitals

References

• Pearson, G.A. (Ed), 2008, Why children die: A pilot study 2006 England (South West, North East and West Midlands), Wales and Northern Ireland. London: CEMACH
   Google Scholar
• Margolis, P., and Gadomski, A., 1998, Does this infant have pneumonia? Journal of the American Medical Association, 279, 308–313
   PubMed Web of Science ®Google Scholar
• Nijman, R.G., Vergouwe, Y., Thompson, M., van Veen, M., van Meurs, A.H.J., van der, Lie, Steyerberg, E.W., Moll, H.A., Oostenbrink, R., 2013, Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: Diagnostic study. British Medical Journal, 346, f1706
   PubMed Web of Science ®Google Scholar
• Rusconi, F., Castagneto, M., Porta, N., Gagliardi, L., Leo, G., Pellegatta, A., Razon, S., Braga, M., 1994, Reference values for respiratory rate in the first 3 years of life. Pediatrics, 94, 350–355
   PubMed Web of Science ®Google Scholar
• Chamberlain, J., Patel, K., Ruttimann, U., Pollack, M., 1998, Pediatric risk of admission (PRISA): A measure of severity of illness for assessing the risk of hospitalization from the emergency department. Annals of Emergency Medicine, 32, 161–169
   PubMed Web of Science ®Google Scholar
• Pollack, M.M., Patel, K.M., and Ruttimann, U.E., 1997, The Pediatric Risk of Mortality III–Acute Physiology Score (PRISM III-APS): A method of assessing physiologic instability for pediatric intensive care unit patients. The Journal of Pediatrics, 131, 575–581
   PubMed Web of Science ®Google Scholar
• Thompson, M., Mayon-White, R., Harnden, A., Perera, R., McLeod, D., Mant, D., 2008, Using vital signs to assess children with acute infections: A survey of current practice. The British Journal of General Practice, 58, 236
   PubMed Web of Science ®Google Scholar
• Krieger, B., Feinerman, D., Zaron, A., Bizousky, F., 1986, Continuous noninvasive monitoring of respiratory rate in critically ill patients. CHEST Journal, 90, 632–634
   PubMed Web of Science ®Google Scholar
• Lovett, P.B., Buchwald, J.M., Stürmann, K., Bijur, P., 2005, The vexatious vital: Neither clinical measurements by nurses nor an electronic monitor provides accurate measurements of respiratory rate in triage. Annals of Emergency Medicine, 45, 68–76
   PubMed Web of Science ®Google Scholar
• Simoes, E., et al., 1991, Respiratory rate: Measurement of variability over time and accuracy at different counting periods. Archives of Disease in Childhood, 66, 1199–1203
   PubMed Web of Science ®Google Scholar
• Johansson, A., 2003, Neural network for photoplethysmographic respiratory rate monitoring. Medical and Biological Engineering and Computing, 41, 242–248
   PubMed Web of Science ®Google Scholar
• Meredith, D.J., Clifton, D., Charlton, P., Brooks, J., Pugh, C.W., Tarassenko, L., 2012, Photoplethysmographic derivation of respiratory rate: A review of relevant physiology. Journal of Medical Engineering & Technology, 36, 1–7
   PubMedGoogle Scholar
• Shah, S.A., 2012, Vital sign monitoring and data fusion for paediatric triage (Oxford, UK: University of Oxford)
   Google Scholar
• Clifton, D., Douglas, J.G., Addison, P.S., Watson, J.N., 2007, Measurement of respiratory rate from the photoplethysmogram in chest clinic patients. Journal of Clinical Monitoring and Computing, 21, 55–61
   PubMedGoogle Scholar
• Fleming, S., Tarassenko, L., Thompson, M., Mant, D., 2008, Non-invasive measurement of respiratory rate in children using the photoplethysmogram. EMBS 2008. 30th Annual International Conference of the IEEE. IEEE Engineering in Medicine and Biology Society, 1886–1889
   Google Scholar
• Fleming, S.G., and Tarassenko, L., 2007, A comparison of signal processing techniques for the extraction of breathing rate from the photoplethysmogram. Int. J. Biol. Med. Sci, 2, 232–236
   Google Scholar
• Foo, J.Y.A., and Wilson, S.J., 2005, Estimation of breathing interval from the photoplethysmographic signals in children. Physiological Measurement, 26, 1049
   PubMed Web of Science ®Google Scholar
• Jin, L., and Jie, J., 2009, Detection of Respiratory Rhythm from Photoplethysmography Signal Using Morphological Operators. 3rd International Conference on Bioinformatics and Biomedical Engineering. Beijing, China
   Google Scholar
• Johnston, W. and Mendelson, Y., 2004, Extracting breathing rate information from a wearable reflectance pulse oximeter sensor. Engineering in Medicine and Biology Society, 2004. IEMBS'04. 26th Annual International Conference of the IEEE. San Francisco, CA, USA
   Google Scholar
• Lee, J., and Chon, K., 2010, Respiratory rate extraction via an autoregressive model using the optimal parameter search criterion. Annals of Biomedical Engineering, 38, 3218–3225
   PubMed Web of Science ®Google Scholar
• Lee, J., and Chon, K.H., 2010, An autoregressive model-based particle filtering algorithms for extraction of respiratory rates as high as 90 breaths per minute from pulse oximeter. IEEE Transactions on Biomedical Engineering, 57, 2158–2167
   PubMed Web of Science ®Google Scholar
• Leonard, P., Grubb, N.R., Addison, P.S., Clifton, D., Watson, J.N., 2004, An algorithm for the detection of individual breaths from the pulse oximeter waveform. Journal of Clinical Monitoring and Computing, 18, 309–312
   PubMedGoogle Scholar
• Leonard, P.A., Clifton, D., Addison, P.S., Watson, J.N., Beattie, T., 2006, An automated algorithm for determining respiratory rate by photoplethysmogram in children. Acta Paediatrica, 95, 1124–1128
   PubMed Web of Science ®Google Scholar
• Madhav, K.V., Ram, M.R., Krishna, E.H., Reddy, K.N., Reddy, K.A., 2011, A robust signal processing method for extraction of respiratory activity from artifact corrupted PPG signal. IEEE Recent Advances in Intelligent Computational Systems (RAICS) 451–456
   Google Scholar
• Nakajima, K., Tamura, T., and Miike, H., 1996, Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique. Medical Engineering & Physics, 18, 365–372
   PubMed Web of Science ®Google Scholar
• Wertheim, D., Olden, C., Symes, L., Rabe, H., Seddon, P., 2013, Monitoring respiration in wheezy preschool children by pulse oximetry plethysmogram analysis. Medical & Biological Engineering & Computing, 51, 965–970
   PubMed Web of Science ®Google Scholar
• Zhou, Y., Zheng, Y., Wang, C., Yuan, J., 2006, Extraction of respiratory activity from photoplethysmographic signals based on an independent component analysis technique: Preliminary report. Instrumentation Science and Technology, 34, 537–545
   Web of Science ®Google Scholar
• Pardey, J., Roberts, S., and Tarassenko, L., 1996, A review of parametric modelling techniques for EEG analysis. Medical Engineering & Physics, 18, 2–11
   PubMed Web of Science ®Google Scholar
• Cazares, S., Moulden, M., Redman, C.W.G., Tarassenko, L., 2001, Tracking poles with an autoregressive model: A confidence index for the analysis of the intrapartum cardiotocogram. Medical Engineering & Physics, 23, 603–614
   PubMed Web of Science ®Google Scholar
• Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.Ch., Mark, R.G., Mietus, J.E., Moody, G.B., C.-Peng, K., Stanley, H.E., 2000, Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals. Circulation, 101, e215–e220
   PubMed Web of Science ®Google Scholar
• Proakis, J.G., 2001, Digital signal processing: Principles algorithms and applications (India: Pearson Education)
   Google Scholar
• Oppenheim, A.V., Schafer, R.W., and Buck, J.R., 1999, Discrete-time signal processing (Upper Saddle River, NJ: Prentice-Hall)
   Google Scholar
• Kay, S.M., and Marple, S.L. Jr., 1981, Spectrum analysis–a modern perspective. Proceedings of the IEEE, 69, 1380–1419
   Web of Science ®Google Scholar
• Marple, S.L., Jr 1987, Digital spectral analysis with applications (Englewood Cliffs, NJ: Prentice-Hall, Inc.). pp. 512
   Google Scholar
• Lee, J., Jung, W., Kang, I., Kim, Y., Lee, G., 2004, Design of filter to reject motion artifact of pulse oximetry. Computer Standards & Interfaces, 26, 241–249
   Web of Science ®Google Scholar
• Neuman, M., and Wang, N., 1990, Motion artifact in pulse oximetry. Proceedings of the Twelfth Annual International Conference of the IEEE. Engineering in Medicine and Biology Society, 12 2007–2008
   Google Scholar
• Rusch, T., Sankar, R., and Scharf, J., 1996, Signal processing methods for pulse oximetry. Computers in Biology and Medicine, 26, 143–159
   PubMed Web of Science ®Google Scholar
• Asada, H.H., Jiang, H.-H., and Gibbs, P., 2004, Active noise cancellation using MEMS accelerometers for motion-tolerant wearable bio-sensors. In: Engineering in Medicine and Biology Society, 2004. IEMBS'04. 26th Annual International Conference of the IEEE. IEEE, San Francisco, CA, USA
   Google Scholar
• Gibbs, P., and Asada, H.H., 2005, Reducing motion artifact in wearable bio-sensors using MEMS accelerometers for active noise cancellation. American Control Conference, 2005. Proceedings of the 2005. IEEE, Portland, OR, USA, 1581–1586
   Google Scholar
• Relente, A., and Sison, L., 2002, Characterization and adaptive filtering of motion artifacts in pulse oximetry using accelerometers. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint. IEEE Engineering in Medicine and Biology, Houston, TX, USA, 2, 1769–1770
   Google Scholar
• Chan, K., and Zhang, Y., 2002, Adaptive reduction of motion artifact from photoplethysmographic recordings using a variable step-size LMS filter. Proceedings of IEEE Sensors, 2, 1343–1346
   Google Scholar
• Coetzee, F.M., and Elghazzawi, Z., 2000, Noise-resistant pulse oximetry using a synthetic reference signal. IEEE Transactions on Biomedical Engineering, 47, 1018–1026
   PubMed Web of Science ®Google Scholar
• Goldman, J.M., Petterson, M.T., Kopotic, R.J., Barker, S.J., 2000, Masimo signal extraction pulse oximetry. Journal of Clinical Monitoring and Computing, 16, 475–483
   PubMed Web of Science ®Google Scholar
• Hayes, M.J., and Smith, P.R., 2001, A new method for pulse oximetry possessing inherent insensitivity to artifact. IEEE Transactions on Biomedical Engineering, 48, 452–461
   PubMed Web of Science ®Google Scholar
• Lee, C., and Zhang, Y., 2003, Reduction of motion artifacts from photoplethysmographic recordings using a wavelet denoising approach. Biomedical Engineering, 2003. IEEE EMBS Asian-Pacific Conference on. IEEE, 194–195
   Google Scholar
• Reddy, K.A., George, B., and Kumar, V.J., 2009, Use of Fourier series analysis for motion artifact reduction and data compression of photoplethysmographic signals. IEEE Transactions on Instrumentation and Measurement, 58, 1706–1711
   Web of Science ®Google Scholar
• Reddy, K.A., and Kumar, V.J., 2007, Motion artifact reduction in photoplethysographic signals using singular value decomposition. IEEE Conference Proceedings on Instrumentation and Measurement Technology. Warsaw, Poland, 1–4
   Google Scholar
• Kim, B.S., and Yoo, S.K., 2006, Motion artifact reduction in photoplethysmography using independent component analysis. IEEE Transactions on Biomedical Engineering, 53, 566–568
   PubMed Web of Science ®Google Scholar
• Krishnan, R., Natarajan, B., and Warren, S., 2008, Analysis and detection of motion artifact in photoplethysmographic data using higher order statistics. Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on. IEEE. Las Vegas, NV. 613–616
   Google Scholar
• Deshmane, A.V., 2009, False arrhythmia alarm suppression using ECG, ABP, and photoplethysmogram (Cambridge, MA, USA: Massachusetts Institute of Technology)
   Google Scholar
• Sukor, J.A., Redmond, S., and Lovell, N., 2011, Signal quality measures for pulse oximetry through waveform morphology analysis. Physiological measurement, 32, 369
   PubMed Web of Science ®Google Scholar
• Weng, J., Ye, Z., and Weng, J., 2006, An improved pre-processing approach for photoplethysmographic signal. IEEE-EMBS 2005. 27th Annual International Conference of the IEEE. Engineering in Medicine and Biology Society, Shanghai, China, 41–44
   Google Scholar
• Gil, E., María Vergara, J., and Laguna, P., 2008, Detection of decreases in the amplitude fluctuation of pulse photoplethysmography signal as indication of obstructive sleep apnea syndrome in children. Biomedical Signal Processing and Control, 3, 267–277
   Web of Science ®Google Scholar
• Hjorth, B, 1970, EEG analysis based on time domain properties. Electroencephalography and Clinical Neurophysiology, 29, 306–310
   PubMedGoogle Scholar
• Li, Q., and Clifford, G., 2012, Dynamic time warping and machine learning for signal quality assessment of pulsatile signals. Physiological Measurement, 33, 1491
   PubMed Web of Science ®Google Scholar
• Selvaraj, N., Jaryal, A., Santhosh, J., Deepak, K.K., Anand, S., 2008, Assessment of heart rate variability derived from finger-tip photoplethysmography as compared to electrocardiography. Journal of Medical Engineering & Technology, 32, 479–484
   PubMedGoogle Scholar
• Bland, J.M., and Altman, D., 1986, Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet, 327, 307–310
   Web of Science ®Google Scholar